Optimal survey design

ABSTRACT

Methods of analyzing and optimizing a seismic survey design are described. Specifically, the sampling quality is analyzed as opposed to the overall quality of the whole survey. This allows for analysis of the impact of the offsets, obstacles, and other aspects of the survey on the sampling quality, which will improve the ability to compress the resulting data and minimize acquisition footprints.

PRIOR RELATED APPLICATIONS

This application is a non-provisional application which claims benefitunder 35 USC §119(e) to U.S. Provisional Application Ser. No. 62/210,270filed Aug. 26, 2015, entitled “OPTIMAL SURVEY DESIGN,” which isincorporated herein in its entirety.

FIELD OF THE DISCLOSURE

The disclosure relates to seismic exploration and processing, and morespecifically to determining the seismic data quality for a plurality oflocations in a given seismic survey.

BACKGROUND OF THE DISCLOSURE

Seismic surveying has become the primary tool of exploration companiesin the continental United States, both onshore and offshore. Seismicsurveying consists of three separate stages: data acquisition, dataprocessing and data interpretation. The success of a seismic prospectingoperation depends on satisfactory completion of all three stages.

A seismic survey is conducted by creating an impulsive or vibratorywave—a seismic wave—on or near the surface of the ground along apredetermined line, using an energy source. The seismic wave travelsinto the earth, is reflected by subsurface formations, and returns tothe surface, where it receivers called geophones—similar tomicrophones—detect the signal and the data recorded. By analyzing thetime it takes for the seismic waves to reflect off of subsurfaceformations and return to the surface, a geophysicist can map subsurfaceformations and anomalies and predict where oil or gas may be trapped insufficient quantities for exploration and development activities.

Until relatively recently, seismic surveys were conducted along a singleline on the ground, and their analysis created a two-dimensional pictureakin to a slice through the earth, showing the subsurface geology alongthat line. This is referred to as two-dimensional or 2D seismic data.

Currently, almost all oil and gas exploratory wells are preceded by 3Dseismic surveys. The basic method of testing is the same as for 2D, butinstead of a single line of energy source points and receiver points,the source points and receiver points are laid out in a grid across theproperty. The receiver points are generally laid down in parallel lines(receiver lines), and the source points are generally laid out inparallel lines that are approximately perpendicular to the receiverlines in most modern surveys, although variations in layout are used.

The spacing of the source and receiver points is determined by thedesign and objectives of the survey. They may be several hundred feetapart or as close as 55 feet or even smaller for high-resolutionsurveys. The resulting recorded reflections received at each receiverpoint come from all directions, and sophisticated computer programs cananalyze this data to create a three-dimensional image of the subsurface.After the data is processed, scientists and engineers assemble andinterpret the 3D seismic information in the form of a 3D data cube thatrepresents a display of subsurface features.

The area covered by the 3D grid must be larger than the subsurface areato be imaged, in order to acquire sufficient data for the area ofinterest. Generally, in order to acquire “full-fold data” for an area,source and receiver points must be laid out to half the spread lengthbeyond the boundary of the area of interest build fold and be full foldat the edge of the area of interest. The additional data acquired inthis “halo” on the outer edge of a 3D survey is sometimes called“tails.” The quality of the subsurface data at the edge of the surveywill not ordinarily be sufficient to map and evaluate the subsurface ofthese “tail” areas.

Additionally, an area around the zone of interest must be added toproperly migrate the data and image it correctly. This zone is calledthe migration apron or aperture and it is at generally greater thenabout 60% of the depth to the primary objective. Thus, even though thearea of interest is small, three zones must be filled—the original areaof interest, the migration apron necessary for the processor to imagethe zone of interest and finally the fold taper that the acquisitionsgroup needs to acquire useable signal to noise ratio data for theprocessor to migrate into the zone of interest.

Seismic data is generally processed for the purpose of imaging seismicreflections for structural and stratigraphic interpretation. The qualityof the seismic data that is ultimately used in the structural andstratigraphic interpretation depends on many different factors andvaries from survey to survey. Steps that are omitted or not correctlycompleted in the data acquisition, data processing and datainterpretation stages can greatly affect the quality of the final imagesor numerical representation of the subsurface features. The quality ofthe seismic data directly affects the reliability of observations andnumerical measurements made from the seismic data and affects anydecisions based on the seismic data.

Constructing accurate seismic images and corresponding earth models isimportant in making business or operational decisions relating to oiland gas exploration and reservoir management. For example, earthscientists use seismic images to determine where to place wells insubterranean regions containing hydrocarbon reservoirs. They also buildmodels of the subsurface to create reservoir models suitable forreservoir fluid flow modeling. The quality of the business andoperational decisions is highly dependent on the quality of the seismicimages and earth models.

The known methods of analyzing the quality of the 3D seismic survey areflawed in some respects. Normally, bin fold maps are created, spiderdiagrams of the azimuth distributions are pulled and/or the partial foldof stack plots on the survey design are reviewed to obtain informationregarding the overall potential for the quality of the survey. Whilethese techniques relate information about the survey as a whole andattributes drawn from them are indicative of the quality of the survey,these techniques do not analyze the sampling of the survey or comparedit to other surveys or take into account the possible variations inactual field implementation of the theoretic survey. Other techniquesinvolve visual inspection of time slices through the fold and offsetplanes of proposed designs. However, the interpretation is influenced bya users experience and knowledge, and thus is somewhat subjective andnot easily compared between users.

There exists a need for a more robust technique for analyzing thequality of a 3D seismic survey, preferably one that is not assubjective.

SUMMARY OF THE DISCLOSURE

Novel methods for analyzing the sampling quality of a 3D seismic surveyare described. The methods allow for improving a given survey and forcomparing different survey designs to improve the quality of the finalsurvey. Thus, the presently disclosed methods address the shortcoming ofthe known methods of analyzing the quality of the 3D seismic survey.

In one embodiment of the novel methods is the use of a common mid point(CMP) array formed from the survey and analyzed to remove nodes and/orartifacts indicative of excessive sampling or no sampling. In a secondembodiment, the entire survey is treated as if it were a single set ofsources and a single set of receivers and one were doing an array studyto understand the geophone and source array interactions. For bothembodiments, different proposed survey designs can then be compared todetermine the potential sampling quality of the final survey.

The common mid point (CMP) method of recording is a universally acceptedmethod in the industry. In CMP recording, waves of seismic energy fromthe source point are reflected to the receiver from a point locatedmidway from the shot and receiver. For 3-D surveys, gathers areconstructed by taking all seismic traces from an area, referred to as a“bin”, around each common midpoint and assigning the traces to thatcommon midpoint. The areal dimensions of the bin are generally half thegroup interval by half the source interval.

One embodiment of the present methods is to take the source and receiverlocations and then sum the responses, offsets, and azimuth relationshipsin the CMP space to form a “CMP array”. This CMP array then undergoesfrequency-wavenumber (F-K) filtering and the resulting spectrum isanalyzed for stacked nodes or sampling artifacts where there is eitherexcessive sampling or no sampling. These nodes and artifacts areminimized to maximize the quality of the survey. This is called the “CMPmethod” herein.

With the CMP method, once the bin-by-bin CMP data is F-K transformed, itcan be interactively analyzed looking for regions that shownon-uniformity of sampling or other artifacts. The data could befiltered by wavenumber to accentuate anomalies, which would then beaddressed in the geographic coordinate space of the source andreceivers. The process would then be iterated so that variability frombin-to-bin is minimized and an optimal survey is designed.

An alternative embodiment is to treat the complete survey as if it werea single set of sources and a single set of receivers and one were doingan array study to understand the geophone and source array interactions.This is called the “Total Survey” method herein. As an example, insteadof a commonly used 12-geophone linear array, one could input in a forexample a 32,000 point full survey receiver location file as an “array”into the geophone array analysis program. At the same time one couldinput a box array of 4 vibrators, thus, one would put in for example all40,000 source point locations from the whole survey as if it were just asingle source point “array”.

The program next would F-K transform the two-dimensional set of receiverand source locations just as if it were a test array for array studies.This way, instead of studying a single source and receiver location likeone would normally do, we treat the complete survey as a single sourceand receiver point and study the whole survey at once.

In the Total Survey method, the typical approach analyzes the wholesurvey at once by taking the source locations for the full survey andF-K transforming them. The process is repeated for the receivers for thefull survey. The two F-K transform spectra (source and receiver) areconsidered for errors in sampling and biases that should/could becorrected in the geographical space. The two transforms can be combinedand then the total survey CMP space can be analyzed for errors orbiases, corrected, and the process repeated for alternative surveydesigns or changes in source and receiver locations in the currentdesign. This approach treats the whole survey as a single entity foranalysis and study of biases.

Both methods include optional steps of quantitatively comparing thefiltered spectrum for two or more survey designs to analyze the qualityof the different designs. This will help a user determine if and how tomove source and/or receiver points or change the design to optimize thedata collection and subsequent analysis.

These embodiments are quite different from the current methodology,which uses stack array concepts where one inputs the field arrays andconvolves them with the source and receiver locations because that showsthe effect at each bin. The currently described methods look at thewhole survey at once, in contrast, allowing comparison and analysis forspatial sampling bias and errors that heretofore had never been seen oraddressed.

In either of the methods, problem areas would be located necessitating areview of the actual pre-plot or as-surveyed locations of the source andreceivers to find a better location and then move the sources, receiversor both to better locations that would reduce whole survey biasesinstead of focusing on local issues. These problem areas are normallydue to obstacles, such as lakes, rivers, no-permit regions, or otherlimits to full access by the seismic crew. The proposed new locationswould be re-inputted into the analysis package as described above andthe results compared to see if the new locations improved or degradedthe biases observed. This is repeated as necessary until an optimalsolution is found.

In either method, the transformed data will be considered for wavenumberand directional biases of the arrays in 2D and 3D representations of theF-K transformed data. Either approach can use conventional geophonearray analysis software to display the data in survey design packagesfor ease of study and interactive filtering.

In another embodiment of the present methods, the source point locationsfor a proposed or a previously acquired survey are entered into thedesign software as a source array. The location of the receiver pointsare also entered as a separate receiver array. The arrays are thentransformed using the F-K transform and studied and compared. Both thebin-by-bin CMP array and the Total Survey arrays are then reviewed forspectral artifacts separately and in a combined mode to see the fulleffect of the whole survey. Any artifact found can then be used to helpin the design of a new survey and the old survey and the new proposedsurvey can be easily compared and displayed. The proposed survey designcan be tuned to improve the quality of the survey by moving thegeographic source and/or received locations. Once the quality and designare acceptable, then seismic data can be acquired (or re-acquired if aproblem is found in a previously executed survey).

One advantage of the present methods is the ability to analyze theimpact of the offsets, obstacles, and other aspects of the survey todetermine the potential sampling quality. The problem with moreconventional approaches like fold, spider plots or triangle plots istheir focus on bin attributes and not the overall actual surfacesampling that leads to spatial aliasing.

A good example of where the present methods improve the survey design isin regard to a sharp inside corner in the survey. Bin attributes withsharp corners are fine and acceptable with nearly the same bin samplingas other areas on the edge of the survey. But, sharp inside cornerscreate migration problems, just as a diffractor does, although theproblem shows up as disruptions spatially instead of in the plane of theseismic data. The solution to the sharp inside corner is more roundedcorners of the survey that do not disrupt the sampling as much. Theinventive methods can identify these areas and problems in the survey,allowing their correction before proceeding with expensive dataacquisition.

The ability to compare multiple designs and/or previous surveys willimprove the final survey. Further, the methods will decrease thepossibility of surface sampling related acquisition footprints. This inturn results in design surveys that are amendable to compressive sensingmethods or techniques.

The data needed for the present methods are the geographical location ofthe source and receivers and the acquisition geometry for each shot thatcontributes to the CMP point that lands in that bin. If one works ingeographic space, sometimes the software is not aware enough of thegeneral DC offset in x and y of the survey so the F-K transform isoffscale. In this case, it is easy to subtract off the x and y locationof the center point of the survey so that loaded geographic data iscentered on the origin of the graph. At this point, it is easilytransformed over as an F-K representation of the survey in both sourceand receiver for further study if using the Total Survey method, or arecursive F-K transform of each shot for each bin in the CMP method andthe data can then summed and presented in the array analysis software.

In more detail, the responses are presented as small glyphs or graphsshowing the power spectrum, ball type F-K plots or full miniature F-K 3Dspectra (see e.g. upper left display in FIG. 3). The method ofpresentation is somewhat dependent upon the software chosen, but the endgoal is the same. A user is looking for zones of localized variabilityfrom the main survey in the CMP method or localized nodes ofnon-uniformity in the Total Survey method.

The F-K filter is preferably a post transform real time interactivefilter that allows a user to adjust the frequency response of the filterand see the effect on the different regions at the same time. These arecommonly available filters in commercial geophysical array designpackages.

Any seismic survey software or add-in can be used with the presentmethods including Omni 3D (Schlumberger), Mesa (Ion Geophysical) andEchos (Paradigm). However, Omni 3D with the seismic survey designpackage is the preferred software because it can handle the large numberof points easily in the 64 bit version of the package. This isespecially important as conventional array design rarely uses over 288geophones and rarely uses over 64 source locations. When loading a wholesurveying data set in as a single geophone or source location, a usermight be inputting tens of thousands of points at once into the program.

Non-geophysical packages like Mathematica (Wolfram Research) or Matlab(Mathworks) can also be used. However, the inventors have found that thetranslation step from each iteration of adjustment to the resulting F-Krepresentation of the whole survey for these packages can make theprocess less efficient. Nonetheless, they are functional in the hereindescribed methods.

Any seismic survey design can be analyzed and compared in the presentmethods. Commonly survey geometries are the parallel, orthogonal, andareal geometry. However, brick-wall geometry (source lines and receiverlines form a brick-wall pattern), slanted geometry (source linesnon-orthogonal to receiver lines) and zigzag geometry (two families ofsource lines making angles of 45° and 135° with the receiver lines) canalso be compared. The different geometries can be compared to determinewhich design offers the best sampling quality for a particularreservoir. Alternative, the positioning of the sources and receivers canbe modified to minimize the appearance of artifacts while stillmaintaining the geometry. Further, the seismic sources and receivers canbe nominally (or about) perpendicular or parallel. An exact right angleis not necessary as slightly non-perpendicular (or non-parallel)geometries also work.

This summary is provided to introduce a selection of concepts that arefurther described below in the detailed description. This summary is notintended to identify key or essential features of the claimed subjectmatter, nor is it intended to be used as an aid in limiting the scope ofthe claimed subject matter.

The distance between adjacent source points along a seismic line is the“source-station spacing.” The distance between adjacent receiver pointsalong a seismic line is the “receiver-station spacing.” Spacing normallydetermines bin size.

As used herein “CMP array” is constructed by taking all of the sourceand receiver pairs associated with every CMP point that lands in aparticular bin, and treating them as if they were a source and receiverarray. These constructed arrays are then analyzed on a bin-by-bin basisfor artifacts.

As used herein “stacking bins” refer to a grid of small, abuttedsubareas that the 3D seismic image is divided into once data iscollected and processed. Each trace in a 3D seismic data volume ispositioned so that it passes vertically through the midpoint of astacking bin. Stacking bins can be square or rectangular, as preferred.Generally, the dimension of a 3D stacking bin in the direction in whichreceiver lines are deployed in a 3D grid is one-half thereceiver-station spacing along these receiver lines, and the dimensionof the stacking bin in the direction in which source lines are orientedis one-half the source-station spacing along the source lines.

The “CMP spacing” is half of the receiver interval. The fold of the CMP(NCMP) is given by the receiver spread length (=number of receivers NGtimes receiver interval ΔxG) and the shot interval ΔxS:

NCMP=NG×ΔxG/(2ΔxS)

As used herein, a “fold” is a measure of the redundancy of commonmidpoint seismic data, equal to the number of offset receivers thatrecord a given data point or in a given bin and are added duringstacking to produce a single trace. Typical values of fold for modernseismic data range from 60 to 2400 for 2D seismic data, and 10 to 1200for 3D seismic data.

As used herein, “stacking” is the process of summing together the tracesso that the coherent primary signal is enhanced by in-phase addition,while source-generated and ambient noise is attenuated by destructiveinterference.

As used herein, “DC offset” is a mean amplitude displacement from zero.In audacity it can be seen as an offset of the recorded waveform awayfrom the center zero point. DC offset is a potential source of clicks,distortion and loss of audio volume.

As used herein, a seismic “artifact” is any distortion in the seismicdata that can impede the ability to accurately estimate reservoirproperties of interest from seismic data.

The term “quality of the coverage” as used herein is intended to meanthe quantitative quality of an attribute of the data associated withparticular portions, such as bins, of the area of a seismic survey.

The term “acquisition footprint” is used to describe amplitude stripesthat appear in time slices or horizon slices produced from 3-D seismicdata volumes.

As used herein, an “offset” refers to the distance from the source pointto a geophone or to the center of a geophone group.

“Normal moveout” or “NMO” refers to effect of the separation betweenreceiver and source on the arrival time of a reflection that does notdip. A reflection typically arrives first at the receiver nearest thesource. The offset between the source and other receivers induces adelay in the arrival time of a reflection from a horizontal surface atdepth.

As used herein, “azimuth” refers to a post-stack attribute thatcomputes, for each trace, the azimuth between the source point and thereceiver point that forms that CMP trace. It is measured in degrees fromnorth normally and varies form 0 to 360 although some look at thedisplays as plus and minus 180 degrees.

As used herein, “node” refers to a single recording station. A “stackednode” refers to group of recording stations at one location.

As used herein, an “F-K filter” or “F-K transform” refers to atwo-dimensional Fourier transform over time and space, where F is thefrequency (Fourier transform over time) and K refers to wave-number(Fourier transform over space). The space dimension is controlled by thetrace spacing and (just like when sampling a time series) must besampled according to the Nyquist criterion to avoid spatial aliasing.The F-K filter is any sort of filter applied to the transformed data inthe transformed F-K space. The F-K transform is the algorithm applied tothe data that actually converts the X-Y conventional sample data intoF-K space for analysis.

As used herein, “sampling” is needed because the use of digital computertechnology means that the analogue signal must be sampled at regularintervals in time in order to be processed. Any signal would beperfectly represented in the computer if an infinite number of sampleswere taken, however, this is impractical. If an insufficient number ofsamples are taken, the higher frequency information is “lost” or“aliased.” The highest frequency f that can be sampled by interval d is1/2d—this is called the “Nyquist Frequency.” Higher frequencies thanthis are said to be temporally aliased because they will appear as ifthey are lower frequencies. If either temporally or spatially aliaseddata are admitted into further processing stages, then artifacts andnoise may well be introduced which could potentially be misleading. Anunderstanding of sampling (particularly spatial sampling) is animportant part of survey design and can affect survey costs and quality.It is obviously important to sample signals correctly, but it is equallyvital to adequately sample noise if this is to be removed by processingroutines.

The use of the word “a” or “an” when used in conjunction with the term“comprising” in the claims or the specification means one or more thanone, unless the context dictates otherwise.

The term “about” means the stated value plus or minus the margin oferror of measurement or plus or minus 10% if no method of measurement isindicated.

The use of the term “or” in the claims is used to mean “and/or” unlessexplicitly indicated to refer to alternatives only or if thealternatives are mutually exclusive.

The terms “comprise”, “have”, “include” and “contain” (and theirvariants) are open-ended linking verbs and allow the addition of otherelements when used in a claim.

The phrase “consisting of” is closed, and excludes all additionalelements.

The phrase “consisting essentially of” excludes additional materialelements, but allows the inclusions of non-material elements that do notsubstantially change the nature of the invention.

The following abbreviations are used herein:

ABBREVIATION TERM CMP Common mid point F-K filter Frequency-wavenumberfilter NMO Normal Moveout

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1. Schematic of method according to the CMP array embodiment.

FIG. 2. Schematic of method according to the Total Survey arrayembodiment.

FIG. 3. Exemplary graphic of step one of the Total Survey arrayembodiment displaying synthetic data and a grid of shots and receiversbefore any artifact correction or optimization. The F-K transformed andfiltered data is shown on the left in a plan view (top) and crosssection view (bottom). The actual layout is shown in the upper right.

FIG. 4A. Display of the impact of the Total Survey array on the sourcesonly at step 1 before any artifact correction or optimization.

FIG. 4B. Display of the sources in FIG. 4A after the first pass ofcleanup of artifacts.

FIG. 4C. Display of the sources in FIG. 4B after a second cleanup usingthe F-K transformation to optimize the spectrum. Compare the impact ofrounding the edges of the lake in the center of the survey to the toFIG. 4A in left FK filtered displays.

FIG. 5A. Display of the receivers at step 1 before any optimization orartifact correction. Note the variability in the FK plan view display inthe upper left panel.

FIG. 5B. Display of the sources in FIG. 5A after the first round ofcleanup of artifacts.

FIG. 5C. Display of the receivers in FIG. 5A after a second (final)round of cleanup using the F-K transformation. Compare the impact ofrounding the edges of the lake in the center of the survey to FIG. 5A inleft FK filtered displays.

FIG. 6. Exemplary graphic of the grid of shots and receivers in FIG. 3after undergoing optimization by the Total Survey method.

DESCRIPTION OF EMBODIMENTS OF THE DISCLOSURE

The disclosure provides a novel method of analyzing a 3D seismic surveyand predicting quality of survey and, optionally, means of improving thequality by adjusting survey design parameters.

The present methods include any of the following embodiments in anycombination(s) of one or more thereof:

-   -   A method of evaluating or optimizing a seismic survey design        comprising, determining the location of a plurality of seismic        sources and a plurality of receivers geographically in a seismic        survey design; summing the responses, offsets, and azimuth        relationships for the locations determined in the first step in        the central midpoint space (CMP); compiling said summed        responses, offsets and azimuth relationships into a CMP array;        applying an F-K transform to said CMP array; applying a        frequency-wavenumber filter to said transformed CMP array;        evaluating the filtered array for artifacts; modifying said        survey design to correct said artifacts; and repeating steps a-f        until an optimal survey is produced, and applying said optimal        seismic survey design to a reservoir.    -   A method of creating or optimizing a seismic survey design for a        hydrocarbon-containing reservoir, comprising: determining the        location of a plurality of seismic sources and a plurality of        receivers in one or more proposed seismic survey designs for a        reservoir being developed; summing the responses, offsets, and        azimuth relationships for the locations determined in step a in        the central midpoint space (CMP) for each proposed seismic        survey design; compiling said summed responses, offsets and        azimuth relationships into a CMP array for proposed seismic        survey design; applying a frequency-wavenumber filter to said        CMP array for each proposed seismic survey design; comparing the        filtered array for artifacts in each proposed seismic survey        design; selecting the proposed seismic survey design with the        minimal artifacts; and applying said selected seismic survey        design to said reservoir.    -   A method of evaluating a seismic survey design comprising,        determining the location of a plurality of seismic sources and a        plurality of receivers geographically in a seismic survey        design; inputting the complete set of sources into an array        design software to form a sources array; inputting the complete        set of receivers into said array design software to form a        receivers array; applying an F-K transform to said sources array        and said receivers array; applying interactive        frequency-wavenumber filters to said sources array and said        receivers array; combining filtered sources array and receivers        array; evaluating the source array, receiver array and the        combined filtered array for artifacts; modifying said survey        design to correct said artifacts and repeating steps a-h until        an optimal survey is produced; and applying said optimal seismic        survey design to a reservoir.    -   A non-transitory machine-readable storage medium, which when        executed by at least one processor of a computer, performs the        steps of any method herein described.    -   Any method as herein described, further comprising the step of        changing one or more locations of one or more seismic sources or        receivers or both to minimize artifacts.    -   Any method as herein described, further comprising comparing        artifacts for two or more survey designs.    -   Any method as herein described, wherein said plurality of        seismic sources or said plurality of receivers or both are about        perpendicular, or about parallel, or both, e.g., orthogonal, but        they can also be non-orthogonal.

One embodiment of the present disclosure is exemplified with respect tothe description below and FIG. 1. However, this is exemplary only of the“CMP method”. The following is intended to be illustrative only, and notunduly limit the scope of the appended claims.

A schematic of the basic steps taken in the described CMP method isshown in FIG. 1. First, test seismic data 101 is collected for aproposed seismic survey design. The source and receiver locations arecombined with the acquisition template to determine the CMP's for eachbin 102 and then used to determine the responses, offsets, and azimuthrelationships in the test data. These relationships are then summed 103in the CMP space to form a CMP array 104.

The CMP array then undergoes transformation using a F-K filter algorithm105 and the responses summed. The summed responses are theninteractively filtered and analyzed as if it were a geophone array usinggeophone array design software to bring out artifacts and other samplingissues in the data 106. The F-K domain will show the artifacts clearlywhereas in the spatial or geographic domain it is more difficult to spotby eye.

The user can then clean up the artifacts by moving the locations of thesource and or receivers geographically to new or better points and thus,improve the quality of the data. Regions containing artifacts arecommonly associated with survey edges, obstacles like railroads, lakesand no permit regions or similar real world encumbrances that naturallydegrade the preferred sampling of the survey.

In addition to analyzing a single survey for artifacts, two or moresurvey designs can be compared to analyze the quality of the differentdesigns. Aspects from each design can then be implemented into the finaldesign. This correction process and then re-collection of the CMP arrayand retransforming with analysis can be repeated until the survey isoptimized. Once the final optimized design is created, data can becollected according to known methods in the art.

In a second embodiment, shown in FIG. 2, the “Total Survey” method, theapproach is similar. Test data is collected and the source and receiverlocations for the whole survey are input into a geophone array designsoftware package 202. The survey sources are then F-K transformed andanalyzed in F-K space for patterns and sampling artifacts 203. The sameapproach is used on the receivers 204. Once each subgroup is handled,the two F-K spectrums are combined in the geophone array analysissoftware 205 and the combined spectrums are analyzed again for anomaliesin sampling and inconsistencies in the whole survey 206. These areiteratively corrected and then the process repeated until the wholesurvey is optimized 207.

Results from using the Total Survey method are shown in FIGS. 3-6 usingexemplary data representing an obstacle encountered during a Barnett 3Dseismic survey near Denton, Tex. in 2012. The obstacle was a no permitzone next to a lake and this example recreates how the problem wasaddressed, while not using the actual survey data. The example data wasloaded into the Omni 3D seismic survey design package for this example.

FIG. 3 displays an example graphic of source and receivers positions,per step 202 of FIG. 2. This organization of display is exemplarily onlyand a user will be able to modify it for his needs. In this particularlayout, the figures are, starting from upper left and moving clockwise,the power spectrum or F-K spectrum in plan view, the sources andreceivers locations and weights with the average actual geographiclocation removed, the derived exemplary wavelet from the convolution ofthe sources and receivers (middle right), the element weights of thearray along the line of analysis (bottom right), the decibel (dB) powerspectrum for the composited array (bottom left) and a cross section viewof the F-K spectrum (middle left).

In FIG. 3, we have mapped a grid of shots and receivers laid out withsome duplication and some gaps that are caused by no permit region and alake of the target area in center of the upper right corner of thedisplay. The plot in the upper left corner is the combined signature ofsource and receiver data. The roughness in this plot is clearly visible.There is a strong grain in both the north-south and east west direction,but that is due to the grid nature. There are also wings and the 45°diagonals caused by the sharp corners caused by the gaps in permitregions.

In the Total Survey Method, step 203 of FIG. 2, requires a user to firsttransform the source data and analyze transform space for artifacts.FIG. 4A-C displays the source data before (4A), after a firsttransformation (4B) and a final, cleaned up source display (4C). In thisexample (and in the real project) we did not actually move points fromthe pre-plotted position. What was done instead, was determine throughthe inventive method, which positions were critical to obtain and wethen worked with the land-owner and seismic crew to obtain access tothese positions and actually acquire some data in the lake during a dryperiod when access became available.

FIG. 4A displays the original source data before any processing. Thelight colored t-shape in the upper right spectrum is due to an areawithout sources because of e.g. lack of permits, rivers, lakes, etc. Thesharp inner edges are problematic because they act as diffractors of thesignal. Thus, the optimization of the design will focus on smoothingthese corners. The smoother the corners, the less disruption insignaling and the more cost effectiveness of the acquisition. While mostwho are skilled at the art recognize that smoother boundaries areprobably a better approach then sharp corners, there has not been anyeasy way prior to the inventive method to parameterize or quantify theimprovements or impact of changes in the survey design.

After processing with the first F-K transformation, the FK spectrum inthe upper left corner has significant changes. FIG. 4B appears to be thebest we can do with the sources and the area we can scan. Sometimes auser just cannot get the permit for the entire plot of land (or in thiscase the lake was too deep to source) so there is a hole in the upperright plot. By rounding the edges off of the hole, but not runninganother transform, we were able to clean up the dark vertical linesinternally in the upper left plot to achieve the display in FIG. 4C.

The next step, step 204, is to analyze just the receivers. The displayfor the receivers is shown in FIG. 5A-C. In the upper left spectrum ofFIG. 5A, the dark lines intersecting in the middle of the spectrum arefrom the sharp corners caused by the no permit zone.

After the first round of transformation, shown in FIG. 5B, the intensityof the dark lines have been reduced. FIG. 5C shows the results after asecond transformation where the artifacts were further attenuated byworking with the seismic crew to obtain some receiver locations in thelake area are effectively rounding the edges of the hole. FIG. 5C is thefinal receiver cleanup. Again, sometimes a no permit zone or lake orriver cannot be fixed and a hole in the upper right spectrum remains.This second transformation made the spectrum as clear as possible androunded the sharp edges.

FIG. 6 demonstrates the final combined results from the fixed source andreceiver data. There is a strong grain in both the north-south and eastwest direction, but that is due to the grid nature of the sources andreceivers. If we had not shot on cardinal orientation (NS-EW) the grainwould be oriented in a different direction. The Total survey method didaddress the wings and the 45° diagonals caused by the sharp cornersshown in FIG. 3 and was able to smooth them out and reduce thedisruption to signal.

This process can be applied over and over to improve and clean up theoverall FK spectrum in the upper left corner of FIG. 3-5, until thesurvey is optimally designed. The final layout of the sources andreceivers can the be performed in the field according to the optimizedsurvey design. Because the no permit areas and means to reduce theartifacts are known in advance, both time and money can be saved usingthe optimized survey design.

Hardware for implementing the inventive methods may preferably includemassively parallel and distributed Linux clusters, which utilize bothCPU and GPU architectures. Alternatively, the hardware may use a LINUXOS, XML universal interface run with supercomputing facilities providedby Linux Networx, including the next-generation Clusterworx Advancedcluster management system.

Another system is the Microsoft Windows 7 Enterprise or Ultimate Edition(64-bit, SP1) with Dual quad-core or hex-core processor, 64 GB RAMmemory with Fast rotational speed hard disk (10,000-15,000 rpm) or solidstate drive (300 GB) with NVIDIA Quadro K5000 graphics card and multiplehigh resolution monitors.

Slower systems could be used but are less preferred since seismic dataprocessing may already compute intensive.

The results may be displayed in any suitable manner, includingprintouts, holographic projections, display on a monitor and the like.Alternatively, the results may be recorded to memory for use with otherprograms, e.g., reservoir modeling, and the like.

The following references are incorporated by reference in theirentirety.

U.S. Pat. No. 7,660,674

1. A method of evaluating a seismic survey design comprising, a)determining the location of a plurality of seismic sources and aplurality of receivers geographically in a seismic survey design; b)summing the responses, offsets, and azimuth relationships for thelocations determined in step 1a in the central midpoint space (CMP); c)compiling said summed responses, offsets and azimuth relationships intoa CMP array; d) applying an F-K transform to said CMP array; e) applyinga frequency-wavenumber filter to said transformed CMP array; f)evaluating the filtered array for artifacts; g) modifying said surveydesign to correct said artifacts; and h) repeating steps a-f until anoptimal survey is produced, and i) applying said optimal seismic surveydesign to a reservoir.
 2. The method of claim 1, further comprising i)changing one or more locations of one or more seismic sources and/orreceivers to minimize artifacts.
 3. The method of claim 1, furthercomprising comparing artifacts for two or more survey designs.
 4. Themethod of claim 1, wherein said plurality of seismic sources and saidplurality of receivers are about perpendicular.
 5. The method of claim1, wherein said plurality of seismic sources and said plurality ofreceivers are not orthogonal.
 6. The method of claim 1, wherein saidplurality of seismic sources and said plurality of receivers are aboutparallel.
 7. The method of claim 2, wherein at least one survey designhas a plurality of seismic sources and said plurality of receivers areabout perpendicular.
 8. The method of claim 2, wherein at least onesurvey design has a plurality of seismic sources and said plurality ofreceivers are about parallel.
 9. The method of claim 2, wherein at leastone survey design has a plurality of seismic sources and said pluralityof receivers are orthogonal.
 10. A method of creating a seismic surveydesign for a hydrocarbon-containing reservoir, comprising: a)determining the location of a plurality of seismic sources and aplurality of receivers in one or more proposed seismic survey designsfor a reservoir being developed; b) summing the responses, offsets, andazimuth relationships for the locations determined in step a in thecentral midpoint space (CMP) for each proposed seismic survey design; c)compiling said summed responses, offsets and azimuth relationships intoa CMP array for proposed seismic survey design; d) applying afrequency-wavenumber filter to said CMP array for each proposed seismicsurvey design; e) comparing the filtered array for artifacts in eachproposed seismic survey design; f) selecting the proposed seismic surveydesign with the minimal artifacts; and g) applying said selected seismicsurvey design to said reservoir.
 11. A method of evaluating a seismicsurvey design comprising, a) determining the location of a plurality ofseismic sources and a plurality of receivers geographically in a seismicsurvey design; b) inputting the complete set of sources into an arraydesign software to form a sources array; c) inputting the complete setof receivers into said array design software to form a receivers array;d) applying an F-K transform to said sources array and said receiversarray; e) applying interactive frequency-wavenumber filters to saidsources array and said receivers array; f) combining filtered sourcesarray and receivers array; g) evaluating the source array, receiverarray and the combined filtered array for artifacts; h) modifying saidsurvey design to correct said artifacts and repeating steps a-h until anoptimal survey is produced; and i) applying said optimal seismic surveydesign to a reservoir.
 12. The method of claim 11, further comprising i)changing one or more locations of one or more seismic sources and/orreceivers to minimize artifacts.
 13. The method of claim 11, furthercomprising comparing artifacts for two or more survey designs.
 14. Themethod of claim 11, wherein said plurality of seismic sources and saidplurality of receivers are about perpendicular.
 15. The method of claim11, wherein said plurality of seismic sources and said plurality ofreceivers are about parallel.
 16. The method of claim 11, wherein saidplurality of seismic sources and said plurality of receivers are aboutorthogonal.
 17. The method of claim 11, wherein said plurality ofseismic sources and said plurality of receivers are non-orthogonal. 18.A non-transitory machine-readable storage medium, which when executed byat least one processor of a computer, performs the steps of the methodof claims 1-17.